code: def test_unary_ops(self, device, dtype):
      data = torch.rand(2, device=device, dtype=dtype)
      x = TensorWrapper(data)
      x1 = TensorWrapper(data)
      x2 = TensorWrapper(data)
  
      self.assert_close(x.add(x), x + x)
      self.assert_close(x.add(1), 1 + x)
      self.assert_close(x.add(1), x + 1)
      self.assert_close(x.mul(x), x * x)
      self.assert_close(x.mul(1), 1 * x)
      self.assert_close(x.mul(1), x * 1)
      self.assert_close(x.sub(x), x - x)
      self.assert_close(x.sub(1), x - 1)
      self.assert_close(x.div(x), x / x)
      self.assert_close(x.true_divide(x), x / x)
      self.assert_close(x.floor_divide(x), x // x)
      self.assert_close(x1.ge(x2), x1 >= x2)
      self.assert_close(x1.gt(x2), x1 > x2)
      self.assert_close(x1.lt(x2), x1 < x2)
      self.assert_close(x1.le(x2), x1 <= x2)
      self.assert_close(x1.eq(x2), x1 == x2)
      self.assert_close(x1.ne(x2), x1 != x2)
      self.assert_close(-x, -data)
  
file_path: kornia/test/core/test_tensor_wrapper.py
imports: import pytest
  import torch
  from kornia.core import Tensor
  from kornia.core.tensor_wrapper import TensorWrapper, unwrap, wrap
  from kornia.testing import BaseTester
label_desc: Use image node_id 5 for calling the TestTensorWrapper obj's underlying member method code with example usage: obj.test_unary_ops(device, dtype) without return types